Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic.

Journal: Journal of medical Internet research
PMID: 32759101

Abstract

BACKGROUND: A novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, which require a preexisting data or knowledge model; however, novel diseases do not have preexisting knowledge models. In an emergent epidemic, language processing can enable rapid conversion of unstructured text to a novel knowledge model. However, although this idea has often been suggested, no opportunity has arisen to actually test it in real time. The current coronavirus disease (COVID-19) pandemic presents such an opportunity.

Authors

  • Antoine Neuraz
    Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche des Cordeliers, UMR 1138 Equipe 22, Paris Descartes, Sorbonne Paris Cité University, Paris, France.
  • Ivan Lerner
    Paris University, Paris, France; AP-HP, DSI-WIND, Paris, France.
  • William Digan
    Hôpital Européen Georges Pompidou, AP-HP, Université Paris Descartes, Université Sorbonne Paris Cité, Paris, France.
  • Nicolas Paris
    AP-HP, DSI-WIND, Paris, France; LIMSI, CNRS, Univ. Paris-Sud, Université Paris-Saclay, F-91405, Orsay, France.
  • Rosy Tsopra
    LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris.
  • Alice Rogier
    Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • David Baudoin
    Centre de Recherche des Cordeliers, INSERM UMRS 1138 Team 22, Université de Paris, Paris, France.
  • Kevin Bretonnel Cohen
    Computational Bioscience Program, University Colorado School of Medicine, Aurora, CO, USA.
  • Anita Burgun
    Hôpital Necker-Enfants malades, AP-HP, Paris, France.
  • Nicolas Garcelon
    Plateforme data science - institut des maladies génétiques Imagine, Inserm, centre de recherche des Cordeliers, UMR 1138 équipe 22, institut Imagine, Paris-Descartes, université Sorbonne- Paris Cité, Paris, France.
  • Bastien Rance
    AP-HP, University Hospital Georges Pompidou; INSERM, UMR_S 1138, Centre de Recherche des Cordeliers, Paris, France.

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